DBMS > Graph Engine vs. HEAVY.AI vs. MarkLogic vs. Prometheus vs. Snowflake

System Properties Comparison Graph Engine vs. HEAVY.AI vs. MarkLogic vs. Prometheus vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Operational and transactional Enterprise NoSQL database

Open-source Time Series DBMS and monitoring system

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Graph DBMS
Key-value store

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.graphengine.io

github.com/heavyai/heavydb
www.heavy.ai

www.marklogic.com

prometheus.io

www.snowflake.com

Technical documentation

www.graphengine.io/docs/manual

docs.heavy.ai

docs.marklogic.com

prometheus.io/docs

docs.snowflake.net/manuals/index.html

Developer

Microsoft

HEAVY.AI, Inc.

MarkLogic Corp.

Snowflake Computing Inc.

Initial release

2010

2016

2001

2015

2014

Current release

5.10, January 2022

11.0, December 2022

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

.NET and C

C++ and CUDA

C++

Server operating systems

.NET

Linux

Linux
OS X
Windows

Linux
Windows

hosted

Data scheme

yes

schema-free

Schema can be enforced

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numeric data only

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Import of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Round robin

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

by Federation

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

can act as a resource manager in an XA/JTA transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, with Range Indexes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control at the document and subdocument levels

Users with fine-grained authorization concept, user roles and pluggable authentication

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